Investigating the association between school substance programs and student substance use: accounting for informative cluster size.

Q3 Mathematics
Epidemiologic Methods Pub Date : 2025-08-26 eCollection Date: 2025-01-01 DOI:10.1515/em-2024-0028
Aya A Mitani, Yushu Zou, Scott T Leatherdale, Karen A Patte
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引用次数: 0

Abstract

Objectives: The use of substances in adolescents is an increasing public health problem. Many high schools in Canada have implemented school-based programs to mitigate student substance use, but their utility is not conclusive. Polysubstance use data collected on students from multiple schools may be subject to informative cluster size (ICS). The objective of this study was to investigate whether a multivariate analysis approach that addresses ICS provides different conclusions from univariate analyses and methods that do not account for ICS.

Methods: We used data from the 2018/2019 cycle of the Cannabis, Obesity, Mental health, Physical activity, Alcohol, Smoking, and Sedentary Behaviour (COMPASS) study, an ongoing prospective cohort study that annually collects data from Canadian high schools and students. We compared results from four analytical approaches that estimate marginal associations between each school substance program and the four substance use behaviours (binge drinking, cannabis, e-cigarette, and cigarette): univariate generalized estimating equations (GEE), univariate cluster-weighted GEE (CWGEE), multivariate GEE, and multivariate CWGEE.

Results: We observed that the proportion of students who engage in each of the four behaviours was higher in small schools and lower in large schools. In general, the univariate and multivariate analyses produced comparable results. Some differences existed between multivariate CWGEE and GEE. CWGEE indicated that the school program on cannabis had an odds ratio (OR) and 95 % confidence interval (CI) of 0.83 (0.73, 0.95) on all substance use, but GEE produced a null association with an OR (95 % CI) of 0.92 (0.79, 1.07).

Conclusions: When ICS is present in clustered school data, weighted and unweighted analyses may produce different results. Care is needed to investigate the relationship between cluster size and the outcome, and use appropriate methods for analysis. Certain substance programs may influence student behaviour in other substances, highlighting the need for a multivariate analytical approach when studying the use of substances by adolescents.

调查学校物质计划和学生物质使用之间的关系:考虑信息簇大小。
目标:青少年吸毒是一个日益严重的公共卫生问题。加拿大的许多高中已经实施了以学校为基础的项目来减少学生的物质使用,但它们的效用并不是决定性的。从多所学校收集的多物质使用数据可能会受到信息性聚类大小(ICS)的影响。本研究的目的是调查针对ICS的多变量分析方法是否与单变量分析和不考虑ICS的方法提供了不同的结论。方法:我们使用了2018/2019周期大麻、肥胖、心理健康、体育活动、酒精、吸烟和久坐行为(COMPASS)研究的数据,这是一项正在进行的前瞻性队列研究,每年收集加拿大高中和学生的数据。我们比较了四种分析方法的结果,这些方法估计了每个学校物质计划与四种物质使用行为(酗酒、大麻、电子烟和香烟)之间的边际关联:单变量广义估计方程(GEE)、单变量聚类加权方程(CWGEE)、多变量广义估计方程(GEE)和多变量CWGEE。结果:我们观察到,参与四种行为的学生比例在小型学校较高,而在大型学校较低。一般来说,单变量和多变量分析产生了可比较的结果。多元CWGEE与GEE之间存在一定的差异。CWGEE表明,学校的大麻项目在所有物质使用方面的优势比(OR)和95 %置信区间(CI)为0.83(0.73,0.95),但GEE产生了零关联,OR(95 % CI)为0.92(0.79,1.07)。结论:当聚集性学校数据中存在ICS时,加权和非加权分析可能产生不同的结果。调查聚类大小与结果之间的关系需要谨慎,并使用适当的分析方法。某些药物方案可能影响学生使用其他药物的行为,这突出表明在研究青少年使用药物时需要采用多变量分析方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Epidemiologic Methods
Epidemiologic Methods Mathematics-Applied Mathematics
CiteScore
2.10
自引率
0.00%
发文量
7
期刊介绍: Epidemiologic Methods (EM) seeks contributions comparable to those of the leading epidemiologic journals, but also invites papers that may be more technical or of greater length than what has traditionally been allowed by journals in epidemiology. Applications and examples with real data to illustrate methodology are strongly encouraged but not required. Topics. genetic epidemiology, infectious disease, pharmaco-epidemiology, ecologic studies, environmental exposures, screening, surveillance, social networks, comparative effectiveness, statistical modeling, causal inference, measurement error, study design, meta-analysis
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